112 citations · 112 across the 3 of their papers we have counts for
3 papers
OptiSeq: Ordering Examples On-The-Fly for In-Context Learning
Rahul Atul Bhope, Praveen Venkateswaran, K. R. Jayaram +3
Developers using LLMs and LLM-based agents in their applications have provided plenty of anecdotal evidence that in-context-learning (ICL) is fragile. In this paper, we show that i…
The Mysterious Case of Neuron 1512: Injectable Realignment Architectures Reveal Internal Characteristics of Meta's Llama 2 Model
Brenden Smith, Dallin Baker, Clayton Chase +6
Large Language Models (LLMs) have an unrivaled and invaluable ability to "align" their output to a diverse range of human preferences, by mirroring them in the text they generate.…
An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
Taylor Sorensen, Joshua Robinson, Christopher Michael Rytting +6
Pre-trained language models derive substantial linguistic and factual knowledge from the massive corpora on which they are trained, and prompt engineering seeks to align these mode…